Evidence map›Paper›PMID 37114132›Full record

SynthesisFrontiers in oncology2023

Diagnostic value of combination of biomarkers for malignant pleural mesothelioma: a systematic review and meta-analysis.

Mucheng Zhu, Zhenhua Lu, Hao Guo, Xiaoting Gu, Defang Wei, Zhengyi Zhang

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mucheng ZhuLanzhou University Second Hospital, Lanzhou University, Lanzhou, China.
Zhenhua LuSchool of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Hao GuoSchool of Medicine, Xiamen University, Xiamen, China.
Xiaoting GuSchool of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Defang WeiSchool of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Zhengyi ZhangLanzhou University Second Hospital, Lanzhou University, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Early-stage accurate diagnosis of malignant pleural mesothelioma (MPM) has always been a formidable challenge. DNA and protein as biomarkers for the diagnosis of MPM have received considerable attention, and yet the outcomes are inconsistent. Methods: In this study, a systematic search employing PubMed, EMBASE, and Cochrane Library to identify relevant studies from the first day of databases to October 2021. Moreover, we adopt the QUADAS-2 to evaluate the quality of eligible studies and Stata 15.0 and Review Manager 5.4 software programs to perform the meta-analysis. Additionally, bioinformatics analysis was performed at GEPIA for the purpose of exploring relationship between related genes and the survival time of MPM patients. Results: We included 15 studies at the DNA level and 31studies at the protein level in this meta-analysis. All results demonstrated that the diagnostic accuracy of the combination of MTAP + Fibulin-3 was the highest with the SEN 0.81 (95% CI: 0.67, 0.89) and the SPE 0.95 (95% CI: 0.90, 0.97). And the bioinformatics analysis indicated that the higher MTAP gene expression level was beneficial to enhance the survival time of MPM patients. Discussion: Nonetheless, as a result of the limitations of the included samples, it may be necessary to conduct additional research before drawing conclusions. Systematic review registration: https://inplasy.com/inplasy-2022-10-0043/, identifier INPLASY2022100043.

Indexed as

bioinformatics analysiscombination of DNA and proteindiagnosticmeta-analysisMPMprognosis

Identifiers

PMID37114132
PMCPMC10126368

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.